Hildrun Kretschmer

The structure of scientific collaboration networks in Scientometrics

The structure of scientific collaboration networks in scientometrics is investigated at the level of individuals by using bibliographic data of all papers published in the international journal Scientometrics retrieved from the Science Citation Index (SCI) of the years 1978–2004. Combined analysis of social network analysis (SNA), co-occurrence analysis, cluster analysis and frequency analysis of words is explored to reveal: (1) The microstructure of the collaboration network on scientists’ aspects of scientometrics; (2) The major collaborative fields of the whole network and of different collaborative sub-networks; (3) The collaborative center of the collaboration network in scientometrics.

Connection and stratification in research collaboration: an analysis of the COLLNET network

Co-authorship among scientists represents a prototype of a social network. By mapping the graph containing all relevant publications of members in an international collaboration network: COLLNET, we infer the structural mechanisms that govern the topology of this social system. The structure of the network affects the information available to individuals, and their opportunities to collaborate. The structure of the network also affects the overall flow of information, and the nature of the scientific community. We present a number of measures of both the macro- (whole-network) and micro- (actor-centered) structure of collaboration, and apply these to COLLNET. We find that this scientific community displays many aspects of a small-world, and is somewhat vulnerable to disruption should major figures become inactive. We also find inequality in the roles played by individuals in the network. The inequalities, however, do not create a closed and isolated core or elite.

Lotka's distribution and distribution of co-author pairs’ frequencies

The original Lotkas Law refers to single scientist distribution, i.e. the frequency of authors Ai with i publications per author is a function of i: Ai=f(i). However, with increasing collaboration in science and in technology the study of the frequency of pairs or triples of co-authors is highly relevant. Starting with pair distribution well-ordered collaboration structures of co-author pairs will be presented, i.e. the frequency of co-author pairs Nij between authors with i publications per author and authors with j publications per author is a function of i and j: Nij=f(i, j) using the normal count procedure for counting i or j. We have assumed that the distribution of co-author pairs’ frequencies can be considered to be reflection of a social Gestalt and therefore can be described by the corresponding mathematical function based on well-known general characteristics of structures in interpersonal relations in social networks. We have shown that this model of social Gestalts can better explain the distribution of co-author pairs than by a simple bivariate function in analogy to Lotkas Law. This model is based on both the Gestalt theory and the old Chinese Yin/Yang theory.

Co-authorship pair distribution patterns by gender

This paper examines impact of gender both on publication productivity and on patterns of scientific collaborations in social sciences in Turkey. The research is based on bibliographic data on national level publications in Turkey. It consists of 7,835 papers written by 6,738 scientists. The findings suggest that (1) there are gender differences at publication productivity, participation, presence and contribution; that (2) there are significantly different tendencies at keeping established co-authorship ties for inter-gender and intra-gender pairs; that (3) there are significant regularities exhibited by coauthor pairs based on each partner author’s publication productivity and findings further show that (4) regularities are different for inter-gender and intra-gender co-authorships. This study contributes to literature by exemplifying an integrated approach to better examine role of gender in scientific collaborations. In addition to descriptive social network analysis methods, it exploits and adopts parametric models from the literature: (1) Social Gestalt theory, a model based on bi-variate distributions of co-author pairs’ frequencies; (2) Lotka’s power law distribution on publication productivity of single authors; (3) Power law distributions of co-author pairs’ frequencies.

Studies in Co-authorship Pairs Distribution: Part-1

There are different versions of counting co-author pairs. We refer to two of them in the present paper including two corresponding hypotheses. Whereas the first version leads to a power function distribution of the co-author pairs the other version shows a bivariate distribution of co-author pairs’ frequencies hence producing threedimensional graphs. The regularities for the second kind of distributions are very different from simple power law distributions. These new regularities may be described by a model for the intensity function of interpersonal attraction (Social Gestalt). Complementarities are a crucial determinant of this model. In conjunction with these complementarities, various shapes of the distribution of observed co-author pairs’ frequencies emerge. As the difference between the two shapes increases, the correlation between these two shapes decreases. After mixing these two shapes a new shape of social Gestalt emerges which can be successfully described with the help of the mathematical function for a social Gestalt. The change of any shape to any other shape of the social Gestalt can be shown by simulation (or morphing). For comparison of two or more shapes the overlay of these shapes into a single frame is possible: either overlay of standardized shapes or of the originals. The present paper is focused on a theoretical approach verified by empirical studies explained in two papers published in this issue (Guo et.al.[1] and Kundra et.al[2]).

Gender bias and explanation models for the phenomenon of women's discriminations in research careers

In the present paper four myths of gender differences in scientific performance are presented and discussed. The persistence of these myths in different forms of evaluation is influencing the women’s discriminations in research careers in combination with effects explained in other explanation models for the existence of the unseen barrier (glass ceiling) that keeps women from rising to the upper levels of the corporate ladder.

Collaboration structures between German immunology institutions, and gender visibility, as reflected in the Web

Very few studies have examined reflection of scientific collaboration networks through coauthorship on the Web. In this paper the collaboration between 80 German institutions of immunology is analyzed, including gender collaboration. Multi-authored papers from 1997 are less visible on the Web in 2004 than the data from 2002. Highly productive institutions have a higher central position in both bibliographic and web collaboration networks and consequently greater influence on the entire scientific community than the less productive institutions. The contribution of female members of the German Society of Immunology in both the networks is very low in relation to that of their male counterparts, which corresponds with general results of a large gender study conducted by the European Commission. Copyright , Beech Tree Publishing.

Distribution of Co-Author Pairs’ Frequencies of the Journal of Biological Chemistry Explained as Social Gestalt

Abstract In single authored bibliographies only single scientist distribution can be found. Wheras in multi-authored bibliographies single scientists distribution, pairs distribution, triples distribution, etc., can be presented. Whith regard to Lotka’s law single scientists P distribution (both in single authored and in multi-authored bibliographies) is of interest. In the future pairs P,Q distribution, triples P,Q,R distribution, etc. should be considered. Starting with pair distribution, the question arises: Is there any regularity or well-ordered structure for the distribution of co-author pairs in the journals on the analogy to Lotka’s law for the distribution of single authors? Usually, “laws” or “regularities” in information science (for example Lotka’s law) have their mathematical descriptions of observed the data in form of functions. The explanations of these phenomena are, however, mostly missing. By contrast, the derivation of a formula for describing the distribution of the number of co-author pairs is presented on the basis of well-known regularities in socio-psychology or sociology in conjunction with Gestalt theory, as an explanation for well-ordered collaboration structures and production of scientific literature. The assumed regularities for the distribution of co-author pairs in journals could be shown in the co-authorship data (1980–1998) of the Journal of Biological Chemistry.

Growth and Structure Formation of Collaboration Patterns Obtained from the Journals PNAS, SCIENCE and the Journal of Experimental Medicine

The paper is focused on social network analysis (SNA) and special structure formation processes of collaboration patterns in scientific networks. Three-dimensional visualization is used to show the growth and structural changes over time in the journals PNAS, Journal of Experimental Medicine and SCIENCE. Self-organization occurs in a variety of complex systems in nature and social networks. We will show this process of self-organization can be found also in co-authorship networks.

The 8th International Conference on Webometrics, Informetrics and Scientometrics & 13th COLLNET Meeting

The 7th International Conference on Webometrics, Informetrics and Scientometrics & 12th COLLNET Meeting took place in Istanbul, Turkey on 20–23 September 2011. This joint meeting was organised under the auspices of the international organisation COLLNET and by the Computer Science Department of the Istanbul Bilgi University with the participation of TUBITAK ULAKBIM (The Turkish Academic Network and Information Centre) and Istanbul Bilgi University Library and Information Center. The event was hosted by the Istanbul Bilgi University. The previous COLLNET meetings, part of which were jointly organised with other events, such as since 8 years with the international conferences on Webometrics, Informetrics and Scientometrics (WIS), had been held in Berlin (Germany) in 2000, New Delhi (India) in 2001, Sydney (Australia) in 2001, Beijing (China) in 2003, Roorkee (India) in 2004, Stockholm (Sweden) in 2005, Nancy (France) in 2006, New Delhi (India) in 2007, Berlin (Germany) in 2008, Dalian (China) in 2009 and Mysore (India) in 2010. The conference attracted about 120 participants from 25 countries. At the conference, about 75 oral presentations and 20 poster presentations were delivered. For the present special issue of Scientometrics we have selected 3 keynotes by Pudovkin, Kretschmer, Stegmann et al. on research evaluation (Part I and II), by Beaver on ‘‘quantity and quality’’,